China recorded 5226 Coronavirus Deaths since the epidemic began, according to the World Health Organization (WHO). In addition, China reported 99256991 Coronavirus Cases. This dataset includes a chart with historical data for China Coronavirus Deaths.

COVID-19: Number of Death: Hubei: True Up data was reported at 1,290.000 Person in 16 Apr 2020. This records an increase from the previous number of 1.000 Person for 05 Apr 2020. COVID-19: Number of Death: Hubei: True Up data is updated daily, averaging 1.000 Person from Feb 2020 (Median) to 16 Apr 2020, with 3 observations. The data reached an all-time high of 1,290.000 Person in 16 Apr 2020 and a record low of -108.000 Person in 13 Feb 2020. COVID-19: Number of Death: Hubei: True Up data remains active status in CEIC and is reported by National Health Commission. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GZ: COVID-19: No of Death.

COVID-19: Number of Death: Year to Date: Hubei data was reported at 4,515.000 Person in 08 Jan 2023. This stayed constant from the previous number of 4,515.000 Person for 07 Jan 2023. COVID-19: Number of Death: Year to Date: Hubei data is updated daily, averaging 4,512.000 Person from Jan 2020 (Median) to 08 Jan 2023, with 1095 observations. The data reached an all-time high of 4,515.000 Person in 08 Jan 2023 and a record low of 1.000 Person in 14 Jan 2020. COVID-19: Number of Death: Year to Date: Hubei data remains active status in CEIC and is reported by National Health Commission. The data is categorized under High Frequency Database’s Disease Outbreaks – Table CN.GZ: COVID-19: No of Death. Clinical diagnosis included in since 12Feb 自2月12日起纳入临床诊断

China recorded 86689 Coronavirus Recovered since the epidemic began, according to the World Health Organization (WHO). In addition, China reported 4636 Coronavirus Deaths. This dataset includes a chart with historical data for China Coronavirus Recovered.

Context

The 2019–20 coronavirus pandemic is an ongoing global pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus first emerged in Wuhan, Hubei, China, in December 2019. On 11 March 2020, the World Health Organization declared the outbreak a pandemic. As of 11 March 2020, over 126,000 cases have been confirmed in more than 110 countries and territories, with major outbreaks in mainland China, Italy, South Korea, and Iran. More than 4,600 have died from the disease and 67,000 have recovered.

Content

2019 Novel Coronavirus (2019-nCoV) is a virus (more specifically, a coronavirus) identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. Early on, many of the patients in the outbreak in Wuhan, China reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients reportedly have not had exposure to animal markets, indicating person-to-person spread is occurring. At this time, it’s unclear how easily or sustainably this virus is spreading between people - CDC

This dataset has information on the number of affected cases, deaths and recovery from 2019 novel coronavirus. Please note that this data was scrapped from https://www.worldometers.info/coronavirus/.This data is solely for education purposes only.

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Acknowledgements

This data is solely belongs to https://www.worldometers.info/coronavirus/. for licensing visit https://www.worldometers.info/licensing/

Context

The novel coronavirus that has infected more than 79,551 people worldwide (as of time of writing this context) is spreading rapidly, and independently, in countries outside of China, including Italy, South Korea, and Iran. The viral illness is being diagnosed among hundreds of people in South Korea, Italy and Iran who have no connection to China.

Content

In the notebook I use the time series data. Time series data columns are described in the column description.

Acknowledgements

Thanks to the Johns Hopkins University for providing this data-set for educational purposes. https://github.com/CSSEGISandData/COVID-19

Inspiration

To visualize COVID-19 spread world wide.

COVID-19: Number of Death: Year to Date: Hubei: Wuhan data was reported at 3,869.000 Person in 13 Dec 2022. This stayed constant from the previous number of 3,869.000 Person for 12 Dec 2022. COVID-19: Number of Death: Year to Date: Hubei: Wuhan data is updated daily, averaging 3,869.000 Person from Jan 2020 (Median) to 13 Dec 2022, with 1069 observations. The data reached an all-time high of 3,869.000 Person in 13 Dec 2022 and a record low of 1.000 Person in 14 Jan 2020. COVID-19: Number of Death: Year to Date: Hubei: Wuhan data remains active status in CEIC and is reported by National Health Commission. The data is categorized under High Frequency Database’s Disease Outbreaks – Table CN.GZ: COVID-19: No of Death. Clinical diagnosis included in since 12Feb 自2月12日起纳入临床诊断

This file contains data on cases and deaths by the new coronavirus in China and the first wave in Italy, collected since May 13. Due to the high amount of contaminated and dead launched in February 13th and April 17th, in China, we redistributed the data, maintaining the original shape of the curve. These data were used to build the epidemiological curves of the countries, aiming to enable the analysis of health management.

Data Overview

This repository contains spatiotemporal data from many official sources for 2019-Novel Coronavirus beginning 2019 in Hubei, China ("nCoV_2019") You may not use this data for commercial purposes. If there is a need for commercial use of the data, please contact Ginkgo Biosecurity, the biosecurity and public health unit of Ginkgo Bioworks at help-epi-modeling@ginkgobioworks.com to obtain a commercial use license.

The incidence data are in a CSV file format. One row in an incidence file contains a piece of epidemiological data extracted from the specified source.

The file contains data from multiple sources at multiple spatial resolutions in cumulative and non-cumulative formats by confirmation status. To select a single time series of case or death data, filter the incidence dataset by source, spatial resolution, location, confirmation status, and cumulative flag.

Data are collected, structured, and validated by Ginkgo's digital surveillance experts. The data structuring process is designed to produce the most reliable estimates of reported cases and deaths over space and time. The data are cleaned and provided in a uniform format such that information can be compared across multiple sources. Data are collected at the time of publication in the highest geographic and temporal resolutions available in the original report.

This repository is intended to provide a single access point for data from a wide range of data sources. Data will be updated periodically with the latest epidemiological data. Ginkgo Biosecurity maintains a database of epidemiological information for over three thousand high-priority infectious disease events (please note: this database was previously maintained by Metabiota; the team responsible joined Ginkgo Biosecurity in August 2022. When using the database, please cite Ginkgo Biosecurity and refer to this repository). Please contact us (help-epi-modeling@ginkgobioworks.com) if you are interested in licensing the complete dataset.

Cumulative vs. Non-Cumulative Incidence

Reporting sources provide either cumulative incidence, non-cumulative incidence, or both. If the source only provides a non-cumulative incidence value, the cumulative values are inferred using prior reports from the same source. Use the CUMULATIVE FLAG variable to subset the data to cumulative (TRUE) or non-cumulative (FALSE) values.

Case Confirmation Status

The incidence datasets include the confirmation status of cases and deaths when this information is provided by the reporting source. Subset the data by the CONFIRMATION_STATUS variable to either TOTAL, CONFIRMED, SUSPECTED, or PROBABLE to obtain the data of your choice.

Total incidence values include confirmed, suspected, and probable incidence values. If a source only provides suspected, probable, or confirmed incidence, the total incidence is inferred to be the sum of the provided values. If the report does not specify confirmation status, the value is included in the "total" confirmation status value.

The data provided under the "Multisource Fusion" often does not include suspected incidence due to inconsistencies in reporting cases and deaths with this confirmation status.

Outcome - Cases vs. Deaths

The incidence datasets include cases and deaths. Subset the data to either CASE or DEATH using the OUTCOME variable. It should be noted that deaths are included in case counts.

Spatial Resolution

Data are provided at multiple spatial resolutions. Data should be subset to a single spatial resolution of interest using the SPATIAL_RESOLUTION variable.

Information is included at the finest spatial resolution provided to the original epidemic report. We also aggregate incidence to coarser geographic resolutions. For example, if a source only provides data at the province-level, then province-level data are included in the dataset as well as country-level totals. Users should avoid summing all cases or deaths in a given country for a given date without specifying the SPATIAL_RESOLUTION value. For example, subset the data to SPATIAL_RESOLUTION equal to "AL0” in order to view only the aggregated country level data.

There are differences in administrative division naming practices by country. Administrative levels in this dataset are defined using the Google Geolocation API (https://developers.google.com/maps/documentation/geolocation/). For example, the data for the 2019-nCoV from one source provides information for the city of Beijing, which Google Geolocations indicates is a "locality.” Beijing is also the name of the municipality where the city Beijing is located. Thus, the 2019-nCoV dataset includes rows of data for both the city Beijing, as well as the municipality of the same name. If additional cities in the Beijing municipality reported data, those data would be aggregated with the city Beijing data to form the municipality Beijing data.

Sources

Data sources in this repository were selected to provide comprehensive spatiotemporal data for each outbreak. Data from a specific source can be selected using the SOURCE variable.

In addition to the original reporting sources, Ginkgo Biosecurity compiles multiple sources to generate the most comprehensive view of an outbreak. This compilation is stored in the database under the source name "Multisource Fusion". The purpose of generating this new view of the outbreak is to provide the most accurate and precise spatiotemporal data for the outbreak. At this time, Ginkgo Biosecurity does not incorporate unofficial - including media - sources into the "Multisource Fusion" dataset.

Quality Assurance

Data are collected by a team of digital surveillance experts and undergo many quality assurance tests. After data are collected, they are independently verified by at least one additional analyst. The data also pass an automated validation program to ensure data consistency and integrity.

NonCommercial Use License

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  Other Rights — In no way are any of the following rights affected by the license: Your fair dealing or fair use rights, or other applicable copyright exceptions and limitations; The author's moral rights; Rights other persons may have either in the work itself or in how the work is used, such as publicity or privacy rights. Notice — For any reuse or distribution, you must make clear to others the license terms of this work. The best way to do this is with a link to this web page.

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Liability

The information is provided “AS IS” and Concentric makes no representations or warranties, express or implied, of any type whatsoever including, without limitation, title, noninfringement, accuracy, completeness, merchantability, or fitness for any particular purpose. Use of proprietary information shall be at the user’s own risk, and Concentric assumes no liability or obligation to the user as a result of use.

Ginkgo Biosecurity shall in no event be liable for any decision taken by the user based on the data made available. Under no circumstances, shall Ginkgo Biosecurity be liable for any damages (whatsoever) arising out of the use or inability to use the database. The entire risk arising out of the use of the database remains with the user.

China COVID-19: Number of Death: New Increase data was reported at 0.000 Person in 10 May 2020. This stayed constant from the previous number of 0.000 Person for 09 May 2020. China COVID-19: Number of Death: New Increase data is updated daily, averaging 8.000 Person from Jan 2020 (Median) to 10 May 2020, with 111 observations. The data reached an all-time high of 254.000 Person in 12 Feb 2020 and a record low of 0.000 Person in 10 May 2020. China COVID-19: Number of Death: New Increase data remains active status in CEIC and is reported by National Health Commission. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GZ: COVID-19: No of Death.

COVID-19: Number of Death: Year to Date: Hubei: Xiangyang data was reported at 40.000 Person in 13 Dec 2022. This stayed constant from the previous number of 40.000 Person for 12 Dec 2022. COVID-19: Number of Death: Year to Date: Hubei: Xiangyang data is updated daily, averaging 40.000 Person from Feb 2020 (Median) to 13 Dec 2022, with 1045 observations. The data reached an all-time high of 40.000 Person in 13 Dec 2022 and a record low of 1.000 Person in 03 Feb 2020. COVID-19: Number of Death: Year to Date: Hubei: Xiangyang data remains active status in CEIC and is reported by National Health Commission. The data is categorized under High Frequency Database’s Disease Outbreaks – Table CN.GZ: COVID-19: No of Death.

COVID-19: Number of Death: Year to Date: Jilin data was reported at 5.000 Person in 08 Jan 2023. This stayed constant from the previous number of 5.000 Person for 07 Jan 2023. COVID-19: Number of Death: Year to Date: Jilin data is updated daily, averaging 3.000 Person from Feb 2020 (Median) to 08 Jan 2023, with 1068 observations. The data reached an all-time high of 5.000 Person in 08 Jan 2023 and a record low of 1.000 Person in 15 May 2020. COVID-19: Number of Death: Year to Date: Jilin data remains active status in CEIC and is reported by National Health Commission. The data is categorized under High Frequency Database’s Disease Outbreaks – Table CN.GZ: COVID-19: No of Death.

This data record contains one dataset deta of 2019-nCOV in China.xlsx, in .xlsx file format.The dataset includes the following information (in 8 separate columns) on the novel coronavirus (2019-nCoV) infection cases in China:-total number of confirmed cases, -total number of suspected cases-total number of cured cases-total number of deaths-total number of new confirmed cases-total number of new suspected cases-total number of new cured cases-total number of new deathsThe number of cases are reported for each day from January 20th to February 21st 2020.Study background, aims and methodology: The 2019–20 coronavirus outbreak is an ongoing public health emergency of international concern involving coronavirus disease 2019 (COVID-19). At the end of December 2019, the epidemic of the novel coronavirus 2019-nCOV infection has spread from the initial place of Wuhan, Huibei province in China, resulting in an epidemic throughout China, with sporadic cases reported globally.The elderly, as well as people with primary diseases, are more likely to die from the infection. Children with chronic kidney disease (CKD), and children on dialysis, are vulnerable, due to their primary diseases and low immunity, especially those who suffer from long-term hormone, immunosuppressive therapy, and maintenance hemodialysis.The aim of this study was to analyse the epidemiological and clinical characteristics of the novel coronavirus, and to explore the infection prevention and control strategies of 2019-nCoV in children with chronic kidney disease (CKD) and children on dialysis.Data were collected from the 2019-nCoV management plan of the National Health Commission of the People’s Republic of China and relevant guidelines. Data on the COVID-19 cases in China, including the number of people, clinical characteristics, effective prevention and control measures from January 20th to February 21st, 2020, and statistical data on CKD in children were collected.

SummaryTotal ever COVID-19 cases and deaths at Maryland congregate living facilities.DescriptionDeprecated as of November 17, 2021.The Outbreak-Associated Cases in Congregate Living data dashboard on coronavirus.maryland.gov was redesigned on 11/17/21 to align with other outbreak reporting. Visit MD COVID-19 Congregate Outbreaks to view Outbreak-Associated Cases in Congregate Living data as reported after 11/17/21.The MD COVID-19 Congregate Cases and Deaths total Summary data layer is the cumulative total of COVID-19 cases and deaths that have occured in nursing homes, assisted living facilities, group homes of 10 or more and state and local facilities. Data are reported to MDH by local health departments, the Department of Public Safety and Correctional Services and the Department of Juvenile Services and are updated once weekly.COVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county.

SummaryThe cumulative number of confirmed COVID-19 deaths among Maryland residents, by date of death.DescriptionThe MD COVID-19 - Total Confirmed Deaths Date of Death data layer is a collection of the statewide confirmed COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by date of death. A death is classified as confirmed if the person had a laboratory-confirmed positive COVID-19 test result. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Probable deaths are available from the MD COVID-19 - Total Probable Deaths by Date of Death data layer.COVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county.

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources:Global: World Health Organization (WHO)U.S.: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This feature layer contains the most up-to-date COVID-19 cases and latest trend plot. It covers China, Canada, Australia (at province/state level), and the rest of the world (at country level, represented by either the country centroids or their capitals)and the US at county-level. Data sources: WHO, CDC, ECDC, NHC, DXY, 1point3acres, Worldometers.info, BNO, state and national government health departments, and local media reports. . The China data is automatically updating at least once per hour, and non-China data is updating hourly. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. This feature layer is supported by Esri Living Atlas team and JHU Data Services. This layer is opened to the public and free to share. Contact us.

Context

From World Health Organization - On 31 December 2019, WHO was alerted to several cases of pneumonia in Wuhan City, Hubei Province of China. The virus did not match any other known virus. This raised concern because when a virus is new, we do not know how it affects people.

So daily level information on the affected people can give some interesting insights when it is made available to the broader data science community.

The European Centre for Disease Prevention and Control released historical data (to 14 December 2020) on the daily number of new reported COVID-19 cases and deaths worldwide.

Content

The attributes of the dataset are the following: 1) dateRep: Date of the report

2) year_week: Week of the year

3) cases_weekly: Number of cases during the week

4) deaths_weekly: Number of deaths during the week

5) countriesAndTerritories: Country/Territory where the data was reported

6) geoId: Country/Territory id

7) countryterritoryCode: Country/Territory code

8) popData2019: Population data of the Country/Territory in 2019

9) continentExp: Continent of the Country/Territory

10) notification_rate_per_100000_population_14-days: 14-day cumulative number of reported COVID-19 cases per 100 000 population

Disclaimer: Population data in the database is taken from Eurostat for Europe and the World Bank for the rest of the world. Disclaimer: Countries that are not listed in these databases have reported no cases to WHO and no cases were identified in the public domain. The formula to calculate the 14-day cumulative number of reported COVID-19 cases per 100 000 population is (New cases over 14 day period)/Population)*100 000.

Acknowledgements

Data obtained from the European Centre for Disease Prevention and Control, an agency of the European Union

Load data into R

#these libraries need to be loaded library(utils) #read the Dataset sheet into “R”. The dataset will be called "data". data <- read.csv("data.csv", na.strings = "", fileEncoding = "UTF-8-BOM")

This open data publication has moved to COVID-19 Statistical Data in Scotland (from 02/11/2022) Novel coronavirus (COVID-19) is a new strain of coronavirus first identified in Wuhan, China. Clinical presentation may range from mild-to-moderate illness to pneumonia or severe acute respiratory infection. This dataset provides information on demographic characteristics (age, sex, deprivation) of confirmed novel coronavirus (COVID-19) cases, as well as trend data regarding the wider impact of the virus on the healthcare system. Data includes information on primary care out of hours consultations, respiratory calls made to NHS24, contact with COVID-19 Hubs and Assessment Centres, incidents received by Scottish Ambulance Services (SAS), as well as COVID-19 related hospital admissions and admissions to ICU (Intensive Care Unit). Further data on the wider impact of the COVID-19 response, focusing on hospital admissions, unscheduled care and volume of calls to NHS24, is available on the COVID-19 Wider Impact Dashboard. There is a large amount of data being regularly published regarding COVID-19 (for example, Coronavirus in Scotland - Scottish Government and Deaths involving coronavirus in Scotland - National Records of Scotland. Additional data sources relating to this topic area are provided in the Links section of the Metadata below. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. All publications and supporting material to this topic area can be found in the weekly COVID-19 Statistical Report. The date of the next release can be found on our list of forthcoming publications. Data visualisation is available to view in the interactive dashboard accompanying the COVID-19 Statistical Report. Please note information on COVID-19 in children and young people of educational age, education staff and educational settings is presented in a new COVID-19 Education Surveillance dataset going forward.

COVID-19: Number of Death: Year to Date: Beijing data was reported at 19.000 Person in 08 Jan 2023. This stayed constant from the previous number of 19.000 Person for 07 Jan 2023. COVID-19: Number of Death: Year to Date: Beijing data is updated daily, averaging 9.000 Person from Jan 2020 (Median) to 08 Jan 2023, with 1078 observations. The data reached an all-time high of 20.000 Person in 19 Dec 2022 and a record low of 1.000 Person in 06 Feb 2020. COVID-19: Number of Death: Year to Date: Beijing data remains active status in CEIC and is reported by National Health Commission. The data is categorized under High Frequency Database’s Disease Outbreaks – Table CN.GZ: COVID-19: No of Death.

BackgroundThe recent emergence and rapid global spread of coronavirus disease 2019 (COVID-19) is leading to public health crises worldwide. Alcohol consumption and cigarette smoking (CS) are two known risk factors in many diseases including respiratory infections.MethodsWe performed a multi-center study in the four largest hospitals designated for COVID-19 patients in Wuhan. There are totally 1547 patients diagnosed with COVID-19 enrolled in the study, alcohol consumption and CS history were evaluated among these patients. The epidemiology, laboratory findings and outcomes of patients contracted COVID-19 were further studied.ResultsOur findings indicated that COVID-19 patients with a history of CS tend to have more severe outcomes than non-smoking patients. However, alcohol consumption did not reveal significant effects on neither development of severe illness nor death rates in COVID-19 patients.ConclusionCS is a risk factor for developing severe illness and increasing mortality during the SARS-CoV-2 infection. We believe that our findings will provide a better understanding on the effects of alcohol intake and CS exposure in COVID-19 patients.